Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-241213220240401On Modeling of Cementation Exponent Using Pore Descriptions in Heterogeneous Carbonate Formations via Robust Intelligent Modeling22071710.22050/ijogst.2025.445375.1705ENAlirezaRostamiDepartment of Petroleum Engineering, Petroleum University of Technology (PUT), Ahwaz, Iran0000-0002-0445-729XAbbasHelalizadehPetroleum Eng.MehdiBahari MoghaddamDepartment of Petroleum Engineering, Petroleum University of Technology (PUT), Ahwaz, Iran0000-0002-8913-5731AboozarSoleymanzadehPetroleum University of Technology, Ahwaz Faculty of PetroleumJournal Article20240223Unlike traditional approaches, Support Vector Regression (SVR), Multilayer Perceptron Neural Network (MLPNN), Probabilistic Neural Network (PNN), Random Forest (RF), Decision Tree (DT), and eXtreme Gradient Boosting (XGBoost) are utilized as predictive algorithms to simulate the cementation exponent based on various pore descriptions and total porosity. To optimize the parameters of the MLPNN approach, Levenberg-Marquardt (LM) is coupled with MLPNN, leading to the development of a hybrid approach named MLPNN-LM. This hybrid model efficiently optimizes neural network parameters, significantly improving accuracy and convergence speed. The necessary databank for constructing, validating, and predicting with the proposed models is derived from Ragland's work and classified into test, validation, and train subsets. The results reveal high precision for the hybrid MLPNN-LM and RF techniques, with key statistical measures such as the Average Absolute Percentage Relative Deviations (AAPRD%) (i.e., the percentage of relative error) of 4.3781% for MLPNN-LM and 4.8690% for RF, and determination coefficients (R²) (i.e., the fitness magnitude of estimated and measured values around Y=X line) of 0.8654 for MLPNN-LM and 0.8731 for RF. The highly accurate estimates of the cementation exponent provided by MLPNN-LM and RF surpass those from commonly applied literature correlations. Sensitivity analysis shows the significant impact of interparticle, moldic, and connected vuggy pore types on the modeling output. The trustworthiness of the databank and the accuracy of the proposed MLPNN-LM and RF approaches are verified by Williams’ plot, with approximately 93.75% and 91.96% of the databank within the applicability domain, respectively. Trend analysis demonstrates a good match of predicted cementation exponent with actual data, especially for deep formations (i.e., depth greater than 1200 m) and tight carbonate reservoirs (i.e., total porosities less than 10%), where traditional correlations face challenges due to the noticeable complexity in the behavior of cementation exponent.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-241213220240401An Optimization Approach for Transportation Process through Lean Logistics: A Case Study of Iran22128510.22050/ijogst.2025.497533.1726ENHodaMoradiDepartment of Management, Meybod University, Meybod, Iran0000-0002-2505-051XSomayeKaramadDepartment of Industrial Management, Yazd Branch, Islamic Azad University, Yazd, Iran.0009-0003-3602-3757Journal Article20250102Optimization of transportation for organizational projects is paramount, as identifying and evaluating transportation barriers constitutes key strategic decisions for managers and decision-makers. This study focuses on three main objectives: identifying the factors influencing lean logistics and transportation barriers, clarifying the interrelationships among the research criteria, and determining their relative importance and ranking in petroleum product distribution. A hybrid model was employed to achieve these objectives. First, the Delphi method was utilized to facilitate the examination of interrelationships among the research criteria. Additionally, fuzzy multi-criteria decision-making techniques, including the fuzzy Analytic Hierarchy Process, were applied to assign specific weights to the criteria. Subsequently, the VIKOR method enabled the prioritization of these criteria. The findings of this study confirm the existence of significant relationships between lean logistics, lean criteria, and transportation barriers, highlighting that managerial barriers and lean managerial logistics are the most critical obstacles and factors, respectively, in petroleum product distribution. These findings can assist managers in improving distribution processes and mitigating key transportation barriers.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-241213220240401Consequence Modeling Analysis of Major Accidents of Process Pipelines22327810.22050/ijogst.2025.508798.1731ENAbdolrahimTaheriAssistant Professor, Petroleum University of Technology0000-0001-6541-0092Mohammad HosseinModhejiM.Sc Student, Department of HSE Engineering, Petroleum University of Technology, Abadan, IranMohsenMotavasselAssistant Professor, Department of Chemical Engineering, Petroleum University of Technology, Abadan, Iran0000-0003-2815-6544Journal Article20250225Process pipelines are essential for operations, but their failures can have severe consequences. This study investigates and analyzes the consequence modeling of the pipeline corridor located in southern Iran. It also determines the restricted and impacted areas around the pipelines using PHAST software. The consequence modeling of the main scenarios, including flammable and toxic gas dispersion, fire, and explosion, is analyzed. According to the results, the restricted and impacted areas around the pipelines are 426.9 meters and 454.3 meters for section 1, and 648 meters and 802 meters for section 2, respectively.<br><br>Following the results, preventive and mitigative measures are recommended to lower risks. Multiple strategies should be employed to reduce the risks associated with the pipelines. Some strategies aim to decrease the frequency of incidents, while others focus on reducing the impacts and consequences of leakage, rupture, or any other type of containment failure.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-241213220240401Cryogenic Simulation and Freezing Point Evaluation in Nitrogen Rejection from Natural Gas: A Coupled Aspen HYSYS–ThermoFAST Approach23956310.22050/ijogst.2026.547495.1752ENMostafaJafariSchool of Chemical Engineering, University of Tehran, Tehran, Iran0009-0003-7514-4850MohammadBanakarDepartment Manager, Engineering and Development Department, Artin Energy Pooya Company, Tehran, IranAliVataniInstitute of Liquefied Natural Gas (I-LNG), School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-4013-1545Journal Article20250916Cryogenic nitrogen rejection from methane-rich natural gas is a critical operation for meeting LNG and pipeline gas specifications. Yet, it is highly susceptible to operational disturbances caused by solid formation in heat exchangers and distillation columns. This study proposes an integrated simulation framework that couples steady-state process modeling in Aspen HYSYS with rigorous solid–liquid–vapor equilibrium (SLVE) analysis in ThermoFAST to evaluate freezing risks in CH4 systematically–N2 mixtures under nitrogen-rejection unit (NRU) conditions. The NRU process, including multi-stream heat exchange, Joule–Thomson expansion, and cryogenic distillation, is modeled using the Peng–Robinson equation of state. ThermoFAST employs a Helmholtz-energy-based PC-SAFT equation of state, together with Lennard-Jones Weeks–Chandler–Andersen (LJ-WCA) pure-solid references, to generate freezing envelopes over a wide pressure range (0.1–10 MPa) and across methane-rich to nitrogen-rich compositions relevant to industrial operations.<br><br>The framework is validated against available experimental solid–liquid equilibrium data, yielding mean absolute and relative deviations of 3.45 K and 5%, respectively, demonstrating its suitability for hazard screening applications. Simulation results reveal that increasing pressure elevates the eutectic temperature and expands the stability region of the solid phase. In contrast, increasing nitrogen concentration depresses the eutectic point and narrows the solid stability range. Risk maps indicate that solid formation is most probable in methane-rich streams (CH4 > 0.75) at pressures of 10 MPa or higher, as well as in nitrogen-rich streams (CH4 < 0.55) at extremely low temperatures, particularly after expansion and in the upper trays of the distillation column. The proposed integrated approach provides a predictive tool for identifying vulnerable operating zones, defining safe temperature–pressure margins, and enhancing the safety, operability, and efficiency of cryogenic nitrogen rejection processes.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-241213220240401Accurate Prediction of Pore Pressure in Hydrocarbon Reservoirs Using Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM)24426210.22050/ijogst.2026.536869.1747ENMahdiehHosseiniUniversity of Tehran, Institute of Geophysics,
North Kargar Ave. TehranMohammad AliRiahiTehran University0000-0002-3827-4467AmirJamabUniversity of Tehran, Institute of Geophysics,
North Kargar Ave. TehranMohammad GhasemFakhariUniversity of Tehran, Institute of Geophysics,
North Kargar Ave. TehranJournal Article20250724Accurate pore pressure estimation is a critical component of geomechanical modeling, essential for maintaining wellbore stability and optimizing drilling fluid density. This study proposes a Grey Wolf Optimizer-Supported Vector Machine (GWO-SVM) workflow to predict pore pressure in a complex carbonate reservoir in southwestern Iran. While traditional empirical correlations like Eaton and Bowers are widely used, their reliance on continuous calibration can be challenging. To address this, discrete Repeating Formation Test (RFT) pressure points were utilized to calibrate baseline empirical trends, creating continuous reference profiles for the entire depth. The GWO-SVM model was then deployed to automate the replication of these calibrated baselines from standard petrophysical logs (sonic, density, resistivity, porosity, and shale volume). Using a dataset from five wells (four for training, one for blind validation), the GWO optimally tuned the Support Vector Regression (SVR) hyperparameters. The model demonstrated exceptional fidelity in replicating the calibrated baseline on the blind test well, achieving an RMSE=37.96psi and an R^2=0.998. Finally, the 1D well-based predictions were integrated into a 3D geostatistical model using co-kriging to visualize pressure compartmentalization influenced by the local tectonic stress regime. This workflow offers a replicable, high-precision alternative for pre-drill pore pressure modeling in data-limited reservoir settings.Petroleum University of TechnologyIranian Journal of Oil and Gas Science and Technology2345-241213220240401Effects of rock elements on enhanced oil recovery by Low-salinity waterflooding test in a limestone formation: A case study in an Iranian oil field24694110.22050/ijogst.2026.368129.1661ENARMINHOSSEINIANDepartment of Petroleum, Mining, and Materials Engineering, CT.C., Islamic Azad University, Tehran, Iran
Post Doctorate Fellowship, Department of Earth Science and Ocean, University of British Columbia, Vancouver, Canada0000-0001-7533-330XMahdiNazariSaremAssistant Professor, Department of Petroleum, Mining, and Materials Engineering, CT.C., Islamic Azad University, Tehran, Iran0000-0002-6444-2890Journal Article20221224The mechanisms of Low-Salinity Water (LSW) flooding in carbonate reservoirs remain less well understood than in sandstones. This study investigates the role of rock composition through a comparative experimental analysis of genuine limestone from the Shadegan oil field and pure synthetic calcite. Core flooding tests, contact angle measurements, zeta potential analysis, and pH monitoring were conducted under reservoir conditions (70°C, 100 bar). Results show that tertiary LSW injection recovered 14.5% of the initial oil in place in limestone, compared to only 3.4% in pure calcite. This significant difference is attributed to a more pronounced wettability shift towards water-wet conditions (42° contact angle reduction vs. 16° in calcite), driven by a stronger negative zeta potential shift (-7.7 mV vs. -4.1 mV) in the genuine rock. XRF analysis revealed the presence of silica, sulfate, and phosphate impurities in the limestone, which amplified the surface charge alteration. The study concludes that trace non-clay minerals significantly enhance LSW efficacy in carbonates, providing new insights for optimizing EOR in complex carbonate formations.